Will Arctic sea ice thickness initialization improve seasonal forecast skill?

被引：125

作者：

Day, J. J. ^{[1
]}

Hawkins, E. ^{[1
]}

Tietsche, S. ^{[1
]}

机构：

[1] Univ Reading, Dept Meteorol, NCAS Climate, Reading, Berks, England

来源：

GEOPHYSICAL RESEARCH LETTERS | 2014年 / 41卷 / 21期

基金：

英国自然环境研究理事会;

关键词：

CLIMATE PREDICTABILITY; ENSEMBLE; MODEL; PREDICTION; EXTENT;

D O I：

10.1002/2014GL061694

中图分类号：

P [天文学、地球科学];

学科分类号：

07 ;

摘要：

Arctic sea ice thickness is thought to be an important predictor of Arctic sea ice extent. However, coupled seasonal forecast systems do not generally use sea ice thickness observations in their initialization and are therefore missing a potentially important source of additional skill. To investigate how large this source is, a set of ensemble potential predictability experiments with a global climate model, initialized with and without knowledge of the sea ice thickness initial state, have been run. These experiments show that accurate knowledge of the sea ice thickness field is crucially important for sea ice concentration and extent forecasts up to 8 months ahead, especially in summer. Perturbing sea ice thickness also has a significant impact on the forecast error in Arctic 2 m temperature a few months ahead. These results suggest that advancing capabilities to observe and assimilate sea ice thickness into coupled forecast systems could significantly increase skill.

引用

页码：7566 / 7575

页数：10

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